Climate change scientists build simplified climate models. They use them to try and predict how earth’s climate will change over time. The problem is, the earth is a very complex system.

So, the models that we build are simplified. The scientists make some assumptions in order to simplify the global system and reduce it down to something we can manage. It’s extremely precarious work. We don’t even fully understand how all the earth’s sub-systems connect to form its overall weather system, so undoubtedly we’re missing some things.

They may be reasonably accurate within certain bounds, but we shouldn’t be prepared to die on a hill defending their infallibility.

Using these models, and applying some fudge factors, climate change “scientists” have predicted disastrous future global warming. They point to data showing that the earth has been heating up, and that this is only the beginning. They claim we must act now to stop further warming because the models show the planet will melt, or something.

But they blame this heat-up on the Industrial Revolution and human action, which unleashed unprecedented compound economic growth of three percent per annum for over 200 years. That slight growth, imperceptible year-to-year, changed the world forever in a very short time frame.

RIVAL METHODS OF DATA ANALYSIS

This coming future warming is supposed to be bad for us.

They’d be perfectly happy if we just shut down all our power plants so that the 2 or 3 percent of us who survived the first 60 days in the ensuing economic meltdown could forage for food for the rest of our lives.

But there are other ways to analyze the data. Statistical analysis is one such way. So are neural networks, which are computer algorithms that model the human brain. They can crunch large numbers and sift almost imperceptible patterns from them in what is called “big data.”

The computer algorithms can analyze large volumes of data in seconds that human minds could never fully grasp or adequately sort…